DeepSeek-R1, a new large language model developed in China, is gaining attention for its promising performance and affordability compared to models like OpenAI’s o1. Released as open-weight, it allows researchers to experiment with the algorithm despite not disclosing the training data. Initial tests demonstrate equivalency in performance across tasks in chemistry, mathematics, and coding, while its lower operational cost encourages broader adoption. As the landscape of large language models expands, DeepSeek offers a compelling alternative to existing frameworks with a more transparent approach to AI.
DeepSeek has released R1 as 'open-weight', allowing researchers to study and build on the algorithm, though its training data remains not fully disclosed.
The openness of DeepSeek is quite remarkable compared to OpenAI's models, which are essentially black boxes and have limited transparency for researchers.
R1 is affordable, costing around one-thirtieth of OpenAI's model, enabling researchers with limited computing power to experiment more freely.
Initial tests show that R1 performs on par with OpenAI’s o1 in various scientific tasks, surprising researchers with its capabilities.
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